Using fertiliser to maintain soil inorganic nitrogen can increase dryland wheat yield with little environmental cost

Agriculture, Ecosystems and Environment 286 (2019) 106644

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Using fertiliser to maintain soil inorganic nitrogen can increase dryland wheat yield with little environmental cost

T

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Chris J. Smitha, , James R. Hunta,1, Enli Wanga, Ben C.T. Macdonalda, Hongtao Xinga,2, O.T. Denmeada, Steve Zeglinb, Zhigan Zhaoa a b

CSIRO Agriculture, PO Box 1700, Canberra, ACT, 2601 Australia CSIRO Oceans and Atmospheres, Canberra, ACT, 2601, Australia

A R T I C LE I N FO

A B S T R A C T

Keywords: N fertilisers Wheat yields Farm profit Soil organic C

Nitrogen (N) deficiency is responsible for a large proportion of the exploitable yield gap that exists in Australian wheat production. In order to maximise N use efficiency (NUE), growers attempt to match N fertiliser to seasonal water limited yield potential, which in the southern grain growing region is largely determined by in-crop rainfall. Australia’s variable rainfall makes water limited yield potential very difficult to predict, and growers tend to under fertilise, fearing economic and environmental losses of N if crops are over-fertilised. However, environmental losses of excess N are low in the semi-arid, winter dominant rainfall environments with high water holding capacity soils that comprise much of the wheat producing regions of south eastern Australia. This is particularly the case when high carbon (C) to N ratio crop residues are retained which facilitate rapid immobilisation of any mineral N surplus to crop requirements. We therefore propose that the exploitable yield gap in wheat could be closed if a longer-term strategy of N fertiliser application was adopted. In this strategy, growers would simply use N fertiliser to maintain an environmentally appropriate base level of inorganic N (N bank) rather than attempting to match fertiliser inputs to seasonal conditions. We used field studies with 15N labelled fertiliser and cropping systems simulations to demonstrate that fertiliser N applied at rates calculated to maintain fixed thresholds of inorganic N (N bank criteria) and top-dressed immediately prior to the period of rapid crop uptake can substantially increase yields and profit in comparison to current practice, even when applications exceed crop demand in some years. A further benefit of this strategy is an increase in soil organic matter. Both field and simulation studies indicate that the environmental cost of such a strategy would be minimal, with only a small increase in leaching and denitrification despite higher overall rates of N application. This strategy needs to be compared with current practices in longer term field experiments to confirm production increases and lack of environmental impacts.

1. Introduction Global crop yield needs to increase at a rate of 1.1–1.2% per annum relative to 2010 levels to satisfy increasing global demand whilst maintaining current prices (Fischer and Connor, 2018). In regions with intensive cropping systems, there is a small gap between farm yields and potential yields and yield gains must be achieved through increases in potential yields (Fischer and Connor, 2018). In other regions with low-input systems, larger yield gaps exist, and farm yields can be brought closer to potential yields through intensification of inputs, such as N fertilizer in the rain-fed wheat cropping systems of the Australian

grain belt (Hochman and Horan, 2018). However, any intensification of the production system must be profitable and sustainable, with no harmful offsite environmental impacts or degradation of the soil resource. Australia produces on average 10% of global wheat exports, and is consequently important for global food security (Fischer et al., 2014). Hochman et al. (2017) estimate that Australian wheat farm yields are currently 55% of water limited potential yield, indicating the existence of an exploitable yield gap. Nitrogen deficiency has long been thought to be a major contributor to the yield gap (Angus, 2001; Hochman et al., 2014; Gobbett et al., 2016; Luo et al., 2017). Hochman and Horan

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Corresponding author. E-mail address: [email protected] (C.J. Smith). 1 Current address: Department of Animal, Plant and Soil Sciences, Centre for AgriBiosciences, 5 Ring Road, La Trobe University, Bundoora, Vic. 3086, Australia. 2 Current address: NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia. https://doi.org/10.1016/j.agee.2019.106644 Received 14 March 2019; Received in revised form 1 August 2019; Accepted 9 August 2019 0167-8809/ © 2019 Elsevier B.V. All rights reserved.

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(2018) estimate that removal of N deficiency would increase national farm wheat yields by 40%. Crop production in south-eastern Australia has historically taken place on ‘mixed’ farms which consist of an integrated wheat (Triticum aestivum) based cropping enterprise and a sheep (Ovis aries) enterprise (Kirkegaard et al., 2011). From the time of European settlement until the middle of the 20th century, the only N source for crop production came from small amounts of biological N2 fixation and mining native soil N reserves (Angus and Grace, 2017). During the middle to the end of the 20th century, crops were commonly grown in sequence with legume-based ley pastures that were able to fix atmospheric N equivalent to the amount exported in grain during the cropping phase, provided legume pastures comprised about half the farm area (Peoples et al., 1998; Angus and Peoples, 2012). Following the collapse of the Australian wool price reserve scheme in 1991 (Bardsley, 1994), the size of the national sheep flock fell from 170 million in 1990 to 68 million in 2010 (ABS, 2013). Farmers either reduced or dispensed with livestock enterprises, and the area planted to pasture contracted accordingly. Over the same period, the area planted to wheat increased from 9 to 13 M ha (ABS, 2013), and there was a rapid increase in average farm wheat yields achieved through a combination of new management and genetic technologies (Kirkegaard and Hunt, 2010). The impact of this change meant that on the majority of Australian cropping farms, biological N2 fixation from pastures was insufficient to support N export in grain, and crops became reliant on fertiliser inputs and mineralisation of soil organic N. Nitrogen fertiliser use on Australian dryland grain crops more than tripled from < 0.4 Mt in 1990 to 1.0 Mt in 2010, and currently stands at 1.4 Mt (Angus and Grace, 2017). Whilst there has also been a substantial increase in the area of grain legumes (which can provide significant amounts of N to subsequent crops, Peoples et al., 2017), at only 5% of cropped area, their contribution to N supply is insufficient to compensate for the decline in legume pasture area (Angus and Grace, 2017). There are several major issues with the increasing reliance on N fertiliser for crop production. Firstly, N fertiliser is a costly input and its use substantially increases cost of production and value-at-risk for growers. Most farmers are mindful of the risks to crop production from frost, heat stress, flooding, and especially rainfall variability, and consequently are conservative in investing in N fertiliser (Asseng et al., 2012). The majority of N fertiliser applied to crops is urea top-dressed during the growing season. Efforts are made to match N fertiliser inputs to seasonal yield potential to maximise nitrogen use efficiency (NUE). This is difficult in southern Australia because of the reliance of yield potential on in-season rainfall (Hunt and Kirkegaard, 2011), and the lack of accurate seasonal rainfall forecasts (Asseng et al., 2012). Consequently, a large yield gap exists in seasons of high water limited yield potential (Hochman et al., 2012). There is evidence that even leading farmers who are achieving economic yield (75–85% of water limited potential yield, van Ittersum et al., 2013v) still under-fertilise, particularly in high rainfall seasons (van Rees et al., 2014v). As well as reducing yields, under-fertilisation results in production of low protein grain, which attracts lower prices for Australian farmers as it exposes them to competition from low cost/low quality producers in the global market (Kingwell et al., 2016a, b). Chronic under-fertilisation also means that soil N balance (defined here as fertiliser plus legume N inputs minus N export in grain and N losses due to leaching, volatilisation and denitrification) becomes negative over time. There is increased reliance on mining soil organic N for crop N supply. Because of the stoichiometric relationship between C and N in soil organic matter (SOM; Kirkby et al., 2013; Richardson et al., 2014), mining soil N also draws down soil organic C (SOC), which has negative consequences for soil structure, water balance, crop production and SOC sequestration (Guo et al., 2012a, b). Many long term cropping experiments conducted in Australia have run negative N balances and show declines in total soil C and N (Dalal and Chan, 2001; Angus and Grace, 2017; Luo et al., 2017), despite most of them

Table 1 The percentage recovery of after harvest. Year

Grain

15

N urea in wheat (2013), barley (2014) and soil

Stem

Leaves

Total Plant

Soil

Soil plus Plant

15 ± 4.7* 2.7 ± 0.4

0.6 ± 0.1

57 ± 9 49 ± 6

34 ± 4 42 ± 5

91 ± 10 91 ± 6

% 2013 2014

a

43 ± 4.8 46 ± 5

a

Mean plus standard deviation. * stubble = stem + leaf.

including no or reduced tillage and retention of crop residues as treatments. In a long term experiment in semi-arid western New South Wales, Fettell and Gill (1995) demonstrated that applications of N fertiliser equivalent to grain N removal were necessary to increase SOC in stubble retained cropping systems. In a similar semi-arid wheat producing system on the Loess plateau of China, Guo et al. (2012a) showed that total soil N and C could be increased under continuous wheat production provided sufficient fertiliser N was applied to offset export in grain. The effect of high N rates on SOC is twofold; firstly, it allows more C to be fixed in plant biomass and provided to the soil as crop roots, exudates and retained residues (Varvel, 1994; Halvorson et al., 1999, 2002), but it also allows C input in biomass to be converted into humus via microbial processes (Kirkby et al., 2014, 2016). Declining levels of organic N further exacerbate the difficulties of N management in semi-arid environments with variable rainfall. In-crop mineralisation is an important source of N for cereal crops and levels of in-crop mineralisation are correlated with in-crop rainfall (Myers, 1984), which also determines water limited potential yield. In-crop mineralisation is therefore able to make N supply self-correcting – larger amounts of N become available in seasons where water limited yield potential and thus crop demand is high. In-crop N mineralisation is also determined by levels of SOM (Myers, 1984; Schjønning et al., 2018), and declining levels of SOM due to N mining remove this adaptive capacity, placing even greater reliance on tactical N fertiliser applications to achieve water limited potential yield. We propose that the gap that exists between farm yields and water limited potential yields in Australia could be substantially reduced if instead of trying to manage N tactically based on seasonal conditions that are difficult if not impossible to predict, a longer-term N management system is used. The long-term N management approach aims to use inputs of fertiliser N to maintain a minimum level of soil inorganic N (N bank) at the onset of rapid crop uptake which is enough to allow water limited potential yields to be achieved in most seasons. This approach considers the amount of inorganic N in the upper section of the soil profile to correct for the carry-over of previously applied N fertiliser not used by the crop in the application year (Feigenbaum et al., 1983; Cui et al., 2013; Yan et al., 2014). It relies on the fact that environmental losses of N are extremely low in stubble retained farming systems in semi-arid environments with winter dominant rainfall and heavier textured soils (Wallace and Armstrong, 2017). Large inputs of carbon (C:N = 80:1) from cereal dominated stubble retained cropping systems immobilise mineral N into organic forms where it is safe from losses and has the potential to mineralise and support crop yield in more favourable seasons. We used a field experiment in southern New South Wales (NSW), Australia, to confirm that in stubble retained semi-arid dryland cropping systems, environmental losses of N are low. The majority of fertiliser N is either taken up by the crop and exported in grain, or immobilised as organic N. We used these experiments to confirm the ability of the crop model APSIM (Holzworth et al., 2014) to simulate the N balance in this environment. We then used APSIM to evaluate the effect of a long-term N strategy with different nominal base levels of inorganic N (N bank criteria) on crop yield and profitability, N losses and soil organic N stocks along a rainfall gradient on light and heavy 2

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Fig. 1. Measured (symbols) and simulated (dashed line) NH4+-N and NO3−-N in the 0–400 mm soil layers at Temora. The vertical bars are the standard deviation. The average NH4+-N or NO3−-N from multiple cores collected from the fertilised, 15N and non-fertilised areas indicate the spatial variability of inorganic N within the large field. Simulated NH4-N or NO3-N should be compared to measured values from the fertilised and 15N plots. Fert_calc and N15_cal are depth weighted average values.

The site has a mean maximum temperature (2000–2016) of 34 °C in January and mean minimum of 2.6 °C in July. Mean annual rainfall (2000–2016) is 467 mm and in 2013 and 2014 was 403 and 499 mm, respectively. Patched point metrological data for the site are available from Queensland Government Department of Science, Information Technology and Innovation (DSITI) and Australian Bureau of Meteorology (https://legacy.longpaddock.qld.gov.au/silo/). The crop sequence at Temora was autumn sown spring wheat in 2012 and 2013 and autumn sown spring barley 2014. Spring wheat (cv EGA Gregory) was sown on 14 May 2013, top dressed with 200 kg/ha of urea (equivalent to 92 kg N/ha) on 6 August and harvested on 18 November 2013. Barley (cv. Scope CL) was sown on 14 May 2014, top dressed with 217 kg/ha of urea (equivalent 100 kg N/ha) and was

textured soils.

2. Material and methods 2.1. Study site and field experiment The field experiment was carried out over 2 years (2013–2014) in a ˜30 ha field 30 (530 m by 560 m) at Temora NSW (Lat: -34.4061; Long: 147.5248). The soil at the site is a Red Chromosol (Isbell, 2002), with a profile number Temora No 913 in the APSoil database (https://www. apsim.info/Products/APSoil.aspx). Plant available water capacity was 167 mm in the upper 1 m of soil and 206 mm to a depth of 1.6 m (Wang et al., 2018). 3

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Fig. 2. Measured and simulated nitrogen accumulation in the biomass and grain of the wheat and barley at Temora. Data for the paddock and the larger 15N plot is shown for the barley.

residue to be determined. The performance of APSIM to simulate the soil water dynamics, evaporation (Et), crop water use, biomass and yield are provided in Wang et al. (2018).

harvested on 10 November 2014. The stubble of the crops were left standing and grazed by sheep during the summer fallow period between crops as per district practice (Hunt et al., 2016). Within the paddock, areas were left unfertilised by the commercial operation and 15N urea (10 atom %) was applied to the wheat and barley on the same date and at the same rate as that used in the rest of the paddock. New 15N urea plots (˜3 by 12 m) were established each year within the area of the crop that received no 14N urea. There were four replicates of each 15N area in each year. Crop and soil samples (0–1.8 m) were taken from within the labelled area of micro-plot at harvest. The crop and soil samples were dried, sub-sampled, finely ground (< 250 μm) and a 0.2 mg sample was used to determine the total N and atom % 15N (Jensen, 1991; Unkovich et al., 2008; Macdonald et al., 2017).

2.4. Soil measurements Nine soil cores (45 mm internal diameter) were collected randomly from the field to measure soil moisture, ammonium (NH4-N), and nitrate (NO3-N) contents in the 0–1.9 m soil layers on 2 May 2013. Once the initial sampling sites were determined, subsequent soil cores were taken within 5 m of the initial location. The cores were sectioned to give 0–100, 100–200, 200–400, 400–600, 600–800, 800–1000, 1000–1300, 1300–1600 and 1600–1900 mm depth increments. The minimum sampling routine involved taking cores at sowing, anthesis and harvest. More intensive sampling was undertaken in 2013, but these cores were taken to a maximum depth of 1.0 m. Cores were taken on 8, 13, 15 and 21 August 2013 to 0.5 m and sectioned to give 0–50, 50–100, 100–200, 200–300, 300–400 and 400–500 mm depth increments. At the sampling on 10 and 11 October 2013, soil cores were taken to 1.0 m depth and sectioned to give 0–50, 50–100, 100–200, 200–300, 300–400, 400–600, 600–800 and 800–1000 mm increments. The wet soil was stored at < 4 °C until extracted. Processing consisted of weighing the total mass of soil in the section, mixing and sub-sampling for mineral N determination. The remaining soil was weighed and dried at 60 °C and converted to an oven dry weight (105 °C) by determining the water content in a sub-set of samples dried at the 60 °C. Gravimetric water contents were converted to volumetric water contents using the total mass of soil and the volume of each section. Nitrate and NH4+-N were determined on field moist samples extracted using a 1:10 ratio of 2 M KCl (Mulvaney, 1996) and analysed colorimeterically on an Alpkem AutoAnalyser.

2.2. Record of onsite rainfall Rainfall data are from 30 min data measured with tipping bucket rain gauges (TB3, Hydrological Services, NSW, Australia) attached to the eddy covariance system and hourly measurement from the cosmicray probe (Wang et al., 2018). Gaps in the data were in-filled by combining both data sources and the site-specific rainfall was used for the simulations. In summary, 263 mm of rain (P) was recorded from 2 May 2013 to the end of the wheat growing season, with 22 mm falling on 16 November 2013 when the wheat was mature. A total of 135 mm was recorded during the fallow period (Nov – 1 April 2013) and 274 mm during the barley growing season of 2014. The periods selected to do the cumulative sums do not match exactly to growing season. Rather, the start and end dates were selected to match the soil coring at the beginning of each phase. 2.3. Crop measurements

2.5. Long term simulations of different N banks Crop measurements were made by cutting 5 adjacent rows, 0.39 m long (0.483 m2) at Z31 (6 August 2013 – wheat; Zadoks et al., 1974; Tottman, 1987), Z37 (29 August 2013), Z75-76 (10 October 2013) and maturity (18 November 2013). Barley was sampled by cutting 4 adjacent rows 0.5 m long at Z32 (14 August 2014), Z65 (anthesis – 24 September 2014) and maturity (7 November 2014). The samples were weighed fresh, and subsamples (approximately 50 stems) separated into components (green and sensed leaves, stem, head and grain). The components from the subsamples were dried at 70 °C, ground and analysed for total N by combustion (C&N analyser). Grain yields were also measured by hand harvesting large areas (> 1.0 m2) of crop and threshing. This allowed total dry matter production, harvest index and

The Agricultural Production Systems SIMulator (APSIM) was used to generate multifactorial N rate simulations for two major soil types at four locations along an east to west rainfall gradient from Griffith to Young, NSW. The annual average rainfall (1954 to 2014) and standard deviation for Griffith was 404 ± 128 mm; Ardlethan, 486 ± 133 mm; Temora, 529 ± 155 mm, and Young, 619 ± 181 mm. The soils used were a Red Chromosol, Temora (APSoil number 913) and a sandy loam near Griffith (APSoil number 697; https://www.apsim.info/Products/ APSoil.aspx). The factorial simulations were run for 60 years (1954 to 2014). Briefly, APSIM is a crop simulation model consisting of modules that 4

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Fig. 3. The response of wheat yield to different N bank criteria for wheat under two soils and 4 climates. Horizontal bars and upper and lower edges of boxes indicate 10%, 25%, 75% and 90%, median (solid line) and mean (dotted line) in the box. The solid circles represent the 5/95th percentile and outliers in the data.

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Fig. 4. Return ratio to N applied to satisfy the N bank criteria for wheat under two soils and 4 climates. The wheat price is adjusted for protein content. Horizontal bars and upper and lower edges of boxes indicate 10%, 25%, 75% and 90%, median (solid line) and mean (dotted line) in the box. The solid circles represent the 5/ 95th percentile.

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Fig. 5. Nitrogen applied to satisfy the N bank criteria for wheat under two soils and 4 climates. Horizontal bars and upper and lower edges of boxes indicate 10%, 25%, 75% and 90%, median (solid line) and mean (dotted line) in the box. The solid circles represent the 5/95th percentile.

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Fig. 6. Effect of growing season rainfall on gross margin ($ ha−1) for the Red Chromosol. The rainfall (1990–2014) was pooled across the 4 climate sequences and analysed for each N bank criteria (symbols). The lines show break point of the linear-plateau response for each N bank criteria.

thereby allowing carry over effects from the previous season to be included in the 61-year period. Gross margins (GM) were calculated as a measure of the profitability of the N bank values (Asseng et al., 2012). Simulated wheat yields were used in the GM calculation. The base price of wheat grain was $250 per Mg (grain protein < 10.5%; Australian $) and adjusted for grain protein. If the grain protein was > 13.0%, the price was $300 per Mg; protein > 11.5 but < 13.0, $290 Mg−1; protein > 10.5 but < 11.5, $270 Mg−1. A basic operating cost of A$150 ha−1 was used which includes costs of seed, fertiliser (other than N fertiliser and N fertiliser application), pesticides, operating of machinery, contractors, crop insurance and interest. The cost of N fertiliser changed depending on the total amount of N applied ($1 kg−1 N). The maximum economic return is to apply N fertiliser until the increase in the GM has a slope of 1 per unit of N applied (Wang et al., 2008, 2009; Asseng et al., 2012). However, farmers adopt a more conservative strategy and N fertiliser is only applied if the additional profit exceeds the N cost by a reasonable margin (e.g. $2; Asseng et al., 2012). For this study, we calculate the increase in the GM per unit of N for the different N criteria for each year. The cumulative discounted cash flow (CDCF) was calculated using an interest rate (i) of 6% (https://en.wikipedia.org/wiki/ Discounted_cash_flow). Cash flow (CF) in each year was calculated from the grain price, yield and grain protein minus operating costs;

simulate crop growth/yield, soil water, soil carbon and nitrogen dynamics within a crop/soil system in response to weather/climate conditions and management practices (Holzworth et al., 2014). APSIM was evaluated at Temora (Wang et al., 2018), and has been tested against a range of field measurements from many different environments (Wang et al., 2009; Xing et al., 2011; Luo et al., 2014; Zhao et al., 2014; Luo et al., 2017). A comprehensive list of publications can be found at https://www.apsim.info/products /publications. The model simulates biomass growth rate using radiation use efficiency (RUE) multiplied by light interception or transpiration efficiency (TE) multiplied by plant water uptake, whichever is smaller. APSIM-SoilWat simulates water movement between soil layers using the tipping-bucket approach. Soil hydraulic parameters (SAT, DUL and LL15) were derived from measured soil water contents from both the TDR and soil sampling at Temora and those reported in APSoil data base. The maximum depth of water uptake by wheat was set at 1.6 m, based on observations at Temora. APSIM-SoilN simulates the soil organic matter decomposition and nitrogen transformation processes in soil in response to changes in soil conditions (mainly temperature and moisture). These processes affect the N availability in soil, and consequently crop growth. Additional information on the APSIM parameterisation are given in Wang et al. (2018). The model includes the many dependencies and interactions between soil N dynamics, soil water, residue decomposition, crop growth, nutrient demand and uptake. Soil organic matter is simulated in the SoilN module which describes the dynamics of both C and N using C: N ratio. Soil C and N are divided into an INERT, BIOM and HUM pool. The BIOM pool represent the more labile soil microbial biomass and microbial products, the INERT pool is considered to be non-susceptible to decomposition, and the HUM pool is the rest of the soil organic matter. Crop residues and roots from fresh organic matter pool (FOM) decompose into the BIOM and HUM pools. The N fertilisation strategy for the simulations was to apply 15 kg N ha−1 (as urea) at sowing and then apply additional N in mid-July to generate total soil inorganic N amounts of 25, 50, 75, 100, 150 and 175 kg N ha-1 (N bank criteria) in the top 0.4 m of soil where most of the N resides. In the model, the soil mineral N pool size was calculated the day before the fertiliser was applied. The amount of fertiliser N applied was calculated as the N bank criteria minus the amount of mineral N (NH4+-N plus NO3–N) in the top 0.4 m of the soil. If the mass of mineral N in the soil at mid-July was greater than a given N bank, no additional fertiliser N was applied. Continuous wheat was simulated (cv. EGA Gregory sown on 25 April in all years) and all crop residues were returned each year. For all simulations, soil N and water were not reset

CDCF = CF1/(1+i)1 + CF2/(1+i)2 +

…

+ CFn/(1+i)n

3. Results and discussion 3.1. Recovery of

15

N urea

The average recovery (soil and plant) of 15N urea applied in 2013 and 2014 was 91 ± 10% and 91 ± 6%, respectively (Table 1). Recovery in the above ground plant material was 57 ± 9% in 2013 and 49 ± 6% in 2014. Less than 3% of the 15N urea was recovered below 0.6 m depth. No ammonia volatilisation was detected. In addition N2O losses were very small (data not presented), and N2 loss based on the unaccounted 15N are ˜ 5–7%. This observation indicates little fertiliser N loss from the soil-plant system in these years, and that NO3-N was mainly assimilated by the crop. Of the 15N fertiliser applied in 2013, 14 ± 4.2% of the 15N remaining in the soil and stubble at the harvest of the wheat was recovered in the barley. Our 15N data suggests limited leaching, evidenced by little 15N recovery below 1 m. Furthermore, the simulations confirm that leaching losses are generally low and unaffected by N application (see below). 8

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Fig. 7. Cumulative Discounted Cash Flow to N applied to satisfy the N bank criteria for wheat under two soils and 4 climates.

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Fig. 8. Effect of N bank criteria on the HUM pool in the surface 0.4 m of a Red Chromosol under 4 climates ( – Ardlethan; – Griffith; -Temora; – Young).

maturity, there was consistency in the predicted and measure N accumulation in the grain. Based on the mineral N dynamics and the crop N accumulation, especially for wheat, the model performance was considered acceptable for simulating the mineral N dynamics, above ground biomass, grain yields and N uptake, along with the soil water dynamics at Temora (Wang et al., 2018). Previously, Huth et al. (2010) concluded that APSIM, if parameterised correctly, was able to predict soil C, water and N in a subtropical agricultural system. Our observation, and previous research (Huth et al., 2010; Luo et al., 2014, 2017) provide confidence in the predictions of the N and water dynamics in southern Australia. It provides us with confidence that the model captures the impact of mineral N and climate variability on crop productivity and changes in soil C and N stocks.

3.2. Validation of APSIM N dynamics There was general agreement between the measured and predicted NH4+-N and - NO3−-N concentrations in the 0–100, 100–200 and 200–400 mm soil layers (Fig. 1). APSIM predicted a peak in NO3−-N concentrations in the 100–200 mm in May –June 2014, and one in the 200–400 mm soil layer in late June. However, no peak in NO3−-N was predicted or observed in the soil below 600 mm. The average NO3-N concentration in the 600–1000 mm soil layer was 1.6 ± 1.9 mg kg-1. The soil sampling did not capture the NO3−-N accumulation in May to June 2014. There was general agreement in predicted soil mineral N values later in the growing season. We consider the predictions of inorganic N (NH4+-N plus NO3−-N) to be adequate, as shown in the 2013 season which had the most frequent measurements. Nitrogen accumulation in the biomass and the grain is shown in Fig. 2. In general, APSIM predicted the N accumulation in the biomass and the grain, especially for the wheat. However, at times there appears to be discrepancies that the sampling frequency of the barley prohibited us from evaluating. During the spring of 2014, the predicted N accumulation was higher than the measured values (Fig. 2); possibly due to the accumulation of NO3−-N in soil in May/June (Fig.1). At crop

3.3. Long term simulations of different N banks 3.3.1. Crop production & profit The response of crop yield to fertiliser application in mid-July to maintain an inorganic N banks in the surface 0.4 m for continuous wheat at locations is given in Fig. 3 (a, b). Crop yields increased with increasing N bank values up to 150 kg N ha−1, after which further 10

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Fig. 9. Effect of N bank criteria on the HUM pool in the surface 0.4 m of a sandy loam over a sandy clay loam soil under 4 climates ( – Ardlethan; – Griffith; –Temora; – Young).

which nationally average 45 kg N ha−1 (Angus and Grace, 2017). The effect of variability in growing season rainfall (March to November), pooled for the four climatic sequences, is given in Fig. 6. We only present results from 1990 to 2014 (Hochman et al., 2017) and for the Red Chromosol soil because the result for the Sandy Loam soil were similar. There was a significant interaction between growing season rainfall and the N bank (P < 0.001). The gross margin increased with N bank (P < 0.001) from about $400 ha−1 at 25 kg N ha−1 to $1603 ha−1and 175 kg N ha−1 across the 4 climate sequences (1990 to 2014). The data tends to have a linear-plateau response with the break point being around 298 ± 7.2 mm of growing season rainfall (across the 4 site) for the N application that generates total soil mineral N of 25 kg N ha−1 across the 4 climate sequences. The split regression accounted for < 20% of the variance in the data. Breakpoints for the rainfall, above which water is not the factor limiting on crop yield, and gross margin across all 4 climates were: 298 ± 7.3, $416 ± 12 (20% of variance), 445 ± 43 mm, $708 ± 34 (30% of the variance), 453 ± 18 mm, $955 ± 42 (35% of the variance); 456 ± 36, $115 ± 64 (39% of the variance); 421 ± 27 mm, $1475 ± 27 (47% of the variance) and 423 ± 25, $1603 ± 77 (50% of the variance) for N application to generate 25, 50, 75, 100, 50 and 175 kg N ha−1 in the top 0.4 m soil. Returns are lower for all N applications in dry seasons (rain < 250 mm) at Griffith and N banks ≥100 kg ha−1 generate low

increases were small. The variation in yield similarly increased with increasing N application, with the largest variation occurring at the highest N application. In wet years, high yield are only achieved with high N applications, however in drier years the high N rates can reduce yield due to crop haying-off (van Herwaarden et al., 1998v). N replete crops also extract more soil water (Gregory et al., 2009) leaving less to carry over to subsequent crops, which will also reduce yield in dry years. The cost of this loss may be more than offset by a higher yielding crop in the preceding year. Return on investment in N fertiliser (return ratio) is reported in Fig. 4. As stated earlier, the ratio was calculated as the average slope of the line between the N criteria. Producers tend to operate closer to 2:1 return ratio (Asseng et al., 2012). Based on the ratio, the optimal N banks are 100 kg N ha−1 for Griffith and Ardlethan and 150 kg N ha−1 at Temora and Young on the Red Chromosol, and 100 kg N ha−1 for Griffith and 150 kg N ha−1 for all other sites on the Sandy Loam. Nitrogen bank above 150 kg N ha−1 could lead to higher crop yields but lower return ratios. In seasons following a low yielding year, less N is applied to achieve the N bank. The variation in the amount of N fertiliser needed to satisfy the N bank increased at the higher N banks, especially at Griffith (Fig. 5). The amounts of N applied in order to optimise return ratios (˜90 to 130 kg N ha−1) are well in excess of current application rates, 11

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Prophet; Hochman et al., 2009; Holzworth et al., 2014), or seasonal forecasts (e.g. Asseng et al., 2012).

Table 2 N balance for wheat for two soils and four locations for climate sequences 1954–2014. Soil

Climate

Red Chromosol Ardlethan

N bank kg N ha−1

25 50 75 100 150 175 Griffith 25 50 75 100 150 175 Temora 25 50 75 100 150 175 Young 25 50 75 100 150 175 Sandy loam over a sandy clay loam Ardlethan 25 50 75 100 150 175 Griffith 25 50 75 100 150 175 Temora 25 50 75 100 150 175 Young 25 50 75 100 150 175

A

S.D.

B

30 53 76 98 138 156 29 50 71 89 118 128 30 53 76 98 141 160 30 54 77 100 145 167

24 27 31 38 50 57 23 28 37 47 66 75 23 25 27 31 43 51 23 24 25 27 31 35

−8 1 7 11 17 20 −7 1 7 10 15 16 −6 4 11 15 21 24 −5 5 13 19 26 29

24 27 31 38 50 57 23 28 37 47 66 75 23 25 27 31 43 51 23 24 25 27 31 35

32 55 78 100 142 160 31 53 74 94 124 133 32 55 79 102 144 164 32 56 80 103 148 170

10 13 21 30 47 56 13 20 31 42 65 74 10 14 20 26 39 48 11 13 17 21 30 37

−3 5 11 14 19 21 −2 6 11 14 18 20 −2 7 13 16 21 23 −2 8 15 19 23 25

10 13 21 30 47 56 13 20 31 42 65 74 10 14 20 26 39 48 11 13 17 21 30 37

N applied

N balance

3.3.2. Soil organic N There was general decline in the mass of N in the HUM pool when the N bank criteria was 25 kg N ha−1 in the surface 0.4 m in mid-July (Figs. 8 and 9). During the initial 10-year period of cropping the Red Chromosol, the HUM pool increased because of residue return; subsequently there was a steady decline in the pool size. The four climate sequences had a small effect on the changes in the HUM N pool. These observations are consistent with general observation that in Australian agro-ecosystems, continuous crop production causes a decline in soil organic N and by association soil organic C (Fettell and Gill, 1995). Many authors attribute decline in soil organic matter to reducing levels of C inputs, however organic C still declines in no-till stubble retained cropping systems with substantial C inputs (Alvarez, 2005; Guo et al., 2012a; Kirkby et al., 2016). We therefore propose after Kirkby et al. (2014) that in the Australian context it is N availability that is limiting the formation of SOM. This is borne out by the results of the simulations - the addition of fertiliser N had the dominant effect on the size of the HUM N pool. Keeping the mineral N pool at, or above 50 kg N ha−1 increased in size of the HUM N pool at all locations. At 50 kg N ha−1, the average N balance over the 61-year period was positive, with values ranging from 1 to 8 kg N ha-1 with a mean of 6.4 kg N ha−1 (Table 2). The rate of increase in HUM N was greater with increasing N additions. In the strategy adopted in these simulations, the N, which is rarely lost from the system other than by grain offtake, is either carried into the following year in mineral form and used by the subsequent crop or immobilised into the organic pool where it gradually becomes available to crops through the process of mineralisation. Consequently, increasing N additions to maintain higher mineral N level in the surface 0.4 m, increases the HUM N pool (Figs. 8 and 9) and the N balance moves further into surplus (Table 2). At higher N criteria, the increase in HUM N was larger at the wetter location (e.g. Young), which presumably reflects higher levels of carbon inputs at the higher yielding site, which become important once N no longer limits humification. Applying N-fertiliser to maintain an established mineral N amount is critical to prevent the depletion of soil total N and the HUM pool (Figs. 8 and 9). Although our lowest N treatment was 25 kg N ha-1, there was a general decline in total soil N; a result consistent with the findings of others. Continuous cropping and crop-fallow systems running a negative N balance cause a decline in soil organic N and C. This has been observed on the Loess Plateau of China (Guo et al., 2012a), western New South Wales (Fettell and Gill, 1995), Midwest USA (Poffenbarger et al., 2017) and the long term Rothamstead experiments (Jenkinson and Rayner, 1977). A review of global studies confirmed this observation to be universal, and that the inverse is also true (Alvarez, 2005). That is, running positive N balances increases soil organic matter when residues are retained. The use of legumes (N fixing), manures and N fertiliser to return a neutral soil N balance is essential for sustainable maintenance of SOM in conservation cropping systems (Fettell and Gill, 1995; Giller et al., 2015). Nitrogen fertilization is likely to increase SOM through increasing inputs of crop residues (roots and straw) that results from improved crop growth (Halvorson et al., 1999), and also increasing rates of humification via increased microbial activity (Kirkby et al., 2016). Our scenario analysis with continuous wheat confirms that highly productive cropping systems supported by N fertiliser can increase soil N stocks. Whilst the application of N to do this is expensive, if farmers aim to achieve > a 2:1 return on investment, soil N level will increase (Figs. 8 and 9). This assumes that other nutrients such phosphorus and sulphur in the soil are not limiting (Kirkby et al., 2014).

S.D.

A N applied = N sowing plus N top dressed; Mean plus standard deviation (S.D.). B N balance = N applied – N grain -N leached; Means plus standard deviation (S.D.).

and even negative returns. However, these were not substantially worse compared to lower N applications, and cumulative discounted cash flow (Fig. 7) for the different N banks indicates that profits in seasons either side of loss years more than compensated. Negative returns were observed at Griffith and Ardlethan. Whilst this clearly demonstrates the enormous potential for accurate seasonal forecasts to allow growers to match N fertiliser to water limited potential yield, current rainfall predictions are likely to provide less than 50% of the value of a perfect forecast (McIntosh et al., 2007) and currently frustrate growers more than they provide value. However, an outstanding question is how the N bank strategy we propose and test here compares to strategies that attempt to match N applications to seasonal yield potential, either using climatology adjusted for growing season conditions to-date (e.g. Yield

3.3.3. Losses of N No NH3 flux was measured in 2013 using circular fertilised areas and the mass balance micro-metrological technique (Denmead, 1983). This result is not surprising given that 6 mm of rain fell after 12

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Fig. 10. Nitrate leached below the root zone for wheat under two soils and 4 climates. Horizontal bars and upper and lower edges of boxes indicate 10%, 25%, 75% and 90%, median (solid lines) and mean (dotted line). The solid circles represent the 5/95th percentile and the outliers.

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nitrogen in the field. In: Freney, J.R., Simpson, J.R. (Eds.), Gaseous Loss of Nitrogen from Plant-Soil Systems. Springer Netherlands, Dordrecht, pp. 133–157. Feigenbaum, S., Seligman, N.G., Benjamin, R.W., Feinerman, D., 1983. Recovery of tagged fertilizer nitrogen applied to rainfed spring wheat (Triticum aestivum L.) subjected to severe moisture stress. Plant Soil 73, 265–274. Fettell, N., Gill, H., 1995. Long-term effects of tillage, stubble, and nitrogen management on properties of a red-brown earth. Aust. J. Exp. Agric. 35, 923–928. Fischer, R.A., Byerlee, D., Edmeades, G.O., 2014. Crop yields and global food security: will yield increase continue to feed the world? ACIAR Monograph No. 158. Australian Centre for International Agricultural Research, Canberra ACT. Fischer, R.A., Connor, D.J., 2018. Issues for cropping and agricultural science in the next 20 years. Field Crops Res. 222, 121–142. Giller, K.E., Andersson, J.A., Corbeels, M., Kirkegaard, J., Mortensen, D., Erenstein, O., Vanlauwe, B., 2015. Beyond conservation agriculture. Front. Plant Sci. 6. Gobbett, D.L., Hochman, Z., Horan, H., Navarro Garcia, J., Grassini, P., Cassman, K.G., 2016. Yield gap analysis of rainfed wheat demonstrates local to global relevance. J. Agric. Sci. 155, 282–299. Gregory, P.J., Shepherd, K.D., Cooper, P.J., 2009. Effects of fertilizer on root growth and water use of barley in northern Syria. J. Agric. Sci. 103, 429–438. Guo, S., Wu, J., Coleman, K., Zhu, H., Li, Y., Liu, W., 2012a. Soil organic carbon dynamics in a dryland cereal cropping system of the Loess Plateau under long-term nitrogen fertilizer applications. Plant Soil 353, 321–332. Guo, S., Zhu, H., Dang, T., Wu, J., Liu, W., Hao, M., Li, Y., Syers, J.K., 2012b. Winter wheat grain yield associated with precipitation distribution under long-term nitrogen fertilization in the semiarid Loess Plateau in China. Geoderma 189–190, 442–450. Halvorson, A., Reule, C.A., Follett, R., 1999. Nitrogen fertilization effects on soil carbon and nitrogen in a dryland cropping system. Soil Sci. Soc. Am. J. 63, 912–917. Halvorson, A.D., Wienhold, B.J., Black, A.L., 2002. Tillage, nitrogen, and cropping system effects on soil carbon sequestration contribution from USDA-ARS. Soil Sci. Soc. Am. J. 66, 906–912. Hochman, Z., Gobbet, D., Holzworth, D., McClelland, T.I., van Rees, H., Marinoni, O., Navarro Garcia, J., Horan, H., 2012. Quantifying yield gaps in rainfed cropping systems: a case study of wheat in Australia. Field Crops Res. 136, 85–96. Hochman, Z., Gobbett, D.L., Horan, H., 2017. Climate trends account for stalled wheat yields in Australia since 1990. Glob. Change Biol. Bioenergy 23, 2071–2081. Hochman, Z., Horan, H., 2018. Causes of wheat yield gaps and opportunities to advance the water-limited yield frontier in Australia. Field Crops Res. 228, 20–30. Hochman, Z., Prestwidge, D., Carberry, P.S., 2014. Crop sequences in Australia’s northern grain zone are less agronomically efficient than implied by the sum of their parts. Agric. Syst. 129, 124–132. Hochman, Z., Van Rees, H., Carberry, P.S., Hunt, J.R., McCown, R.L., Gartmann, A., Holzworth, D., Van Rees, S., Dalgliesh, N.P., Long, W., Peake, A.S., Poulton, P.L., 2009. Re-inventing model-based decision support with Australian dryland farmers: 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate. Crop Pasture Sci. 60, 1057–1070. Holzworth, D.P., Huth, N.I., deVoil, P.G., Zurcher, E.J., Herrmann, N.I., McLean, G., Chenu, K., van Oosterom, E.J., Snow, V., Murphy, C., Moore, A.D., Brown, H., Whish, J.P.M., Verrall, S., Fainges, J., Bell, L.W., Peake, A.S., Poulton, P.L., Hochman, Z., Thorburn, P.J., Gaydon, D.S., Dalgliesh, N.P., Rodriguez, D., Cox, H., Chapman, S., Doherty, A., Teixeira, E., Sharp, J., Cichota, R., Vogeler, I., Li, F.Y., Wang, E., Hammer, G.L., Robertson, M.J., Dimes, J.P., Whitbread, A.M., Hunt, J., van Rees, H., McClelland, T., Carberry, P.S., Hargreaves, J.N.G., MacLeod, N., McDonald, C., Harsdorf, J., Wedgwood, S., Keating, B.A., 2014. APSIM - evolution towards a new generation of agricultural systems simulation. Environ. Model. Softw. 62, 327–350. Hunt, J.R., Kirkegaard, J.A., 2011. Re-evaluating the contribution of summer fallow rain to wheat yield in southern Australia. Crop Pasture Sci. 62, 915–929. Hunt, J.R., Swan, A.D., Fettell, N.A., Breust, P.D., Menz, I.D., Peoples, M.B., Kirkegaard, J.A., 2016. Sheep grazing on crop residues do not reduce crop yields in no-till, controlled traffic farming systems in an equi-seasonal rainfall environment. Field Crops Res. 196, 22–32. Huth, N.I., Thorburn, P.J., Radford, B.J., Thornton, C.M., 2010. Impacts of fertilisers and legumes on N2O and CO2 emissions from soils in subtropical agricultural systems: a simulation study. Agric. Ecosyst. Environ. 136, 351–357. Isbell, R.F., 2002. The Australian Soil Classification - Revised Edition. CSIRO Publishing, Collingwood, Australia. Jenkinson, D.S., Rayner, J.H., 1977. The turnover of soil organic matter in some of the Rothamsted classical experiments. Soil Sci. 123, 298–305. Jensen, E.S., 1991. Evaluation of automated analysis of 15N and total N in plant material and soil. Plant Soil 133, 83–92. Kingwell, R., Carter, C., Elliot, P., White, P., 2016a. Russia’s Wheat Industry: Implications for Australia. AEGIC, South Perth. Kingwell, R., Elliot, P., White, P., Carter, C., 2016b. Ukraine: an Emerging Challenge for Australian Wheat Exports. AEGIC, South Perth. Kirkby, C.A., Richardson, A.E., Wade, L.J., Batten, G.D., Blanchard, C., Kirkegaard, J.A., 2013. Carbon-nutrient stoichiometry to increase soil carbon sequestration. Soil Biol. Biochem. 60, 77–86. Kirkby, C.A., Richardson, A.E., Wade, L.J., Conyers, M., Kirkegaard, J.A., 2016. Inorganic nutrients increase humification efficiency and C-Sequestration in an annually cropped soil. PLoS One 11. Kirkby, C.A., Richardson, A.E., Wade, L.J., Passioura, J.B., Batten, G.D., Blanchard, C., Kirkegaard, J.A., 2014. Nutrient availability limits carbon sequestration in arable soils. Soil Biol. Biochem. 68, 402–409. Kirkegaard, J.A., Hunt, J.R., 2010. Increasing productivity by matching farming system management and genotype in water-limited environments. J. Exp. Bot. 61, 4129–4143. 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topdressing and a further 2.2 mm on the following day. The simulations predicted N losses from nitrification (N2O) and denitrification (N2O plus N2) of 0.3 and 0.9 kg N ha−1 in June of 2013 and 2014, respectively. No other denitrification events were predicted by the model. The low N loss from denitrification is consistent with the high recovery of the 15N fertiliser (see above). When these two lines of evidence are considered together, N loss from denitrification is considered to be minimal in these years and is captured by the model. Leaching however is episodic, as shown by the outliers in the simulation output (Fig. 2). Large amounts (> 30 but < 60 kg N ha−1) can be leached in the wetter year of the climate sequence (1954–2014). These larger leaching events occur in < 3 years in the 61-year climatic sequence. Furthermore, in wetter years, the amount of N leached shows an increase with increasing N application, especially on the sandy loam profile near Griffith (Fig. 10). The median annual N leaching, for all N rates and two soils was low, ˜ 0.84 (range: 0.0–3.2) kg N ha-1 for the climate sequence 1954–2014, and 0.6 (0–2.2) kg N ha−1 for the climate sequence 1990-2014. 4. Conclusion Field studies using 15N labelled urea demonstrated that fertiliser N losses are low in stubble retained cropping systems in semi-arid south eastern Australia. The majority of N is either taken up by the crop in the year of application, remains in mineral form for subsequent crops, or is immobilised into the organic N pool resulting in improved soil fertility. APSIM can adequately simulate N dynamics in the study environment. The use of a fertiliser strategy that maintains a base level of soil fertility (N bank) could simultaneously increase yields, farm profits and soil C and N stocks. The appropriate level of N bank required to optimise production and profit whilst minimising losses varied with rainfall environment and is related to longer term rather than current season water limited yield potential. We conclude that a long-term N management strategy that maintains a base level of fertility has the potential to substantially increase Australian farm wheat yields and maintain or improve soil N & C reserves whilst causing little in the way of environmental damage. Medium to long term field experiments with grower involvement are required to verify these findings and facilitate on-farm adoption. Acknowledgements We acknowledge the support from CSIRO Agriculture, the AustraliaChina Joint Research Centre – Healthy Soils for Sustainable Food Production and Environmental Quality (ACSRF48165), and the CSIRO and Chinese Academy of Agricultural Sciences (CAAS) through the research project ‘Scientific benchmarks for sustainable agricultural intensification’ for their financial supports. References ABS, 2013. 7124.0 - Historical Selected Agriculture Commodities, by State (1861 to Present), 2010-11. Australian Bureau of Statistics, Canberra. Alvarez, R., 2005. A review of nitrogen fertilizer and conservation tillage effects on soil organic carbon storage. Soil Use Manage. 21, 38–52. Angus, J.F., 2001. Nitrogen supply and demand in Australian agriculture. Aust. J. Exp. Agric. 41, 277–288. Angus, J.F., Grace, P.R., 2017. Nitrogen balance in Australia and nitrogen use efficiency on Australian farms. Soil Res. 55, 435–450. Angus, J.F., Peoples, M.B., 2012. Nitrogen from Australian dryland pastures. Crop Pasture Sci. 63, 746–758. Asseng, S., McIntosh, P.C., Wang, G., Khimashia, N., 2012. Optimal N fertiliser management based on a seasonal forecast. Eur. J. Agron. 38, 66–73. Bardsley, P., 1994. The collapse of the Australian wool reserve price scheme. Econ. J. 104, 1087–1105. Cui, Z., Chen, X., Zhang, F., 2013. Development of regional nitrogen rate guidelines for intensive cropping systems in China. Agron. J. 105, 1411–1416. Dalal, R.C., Chan, K.Y., 2001. Soil organic matter in rainfed cropping systems of the Australian cereal belt. Soil Res. 39, 435–464. Denmead, O.T., 1983. Micrometeorological methods for measuring gaseous losses of

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